cpo-advisor

name	cpo-advisor
description	Product leadership for scaling companies. Product vision, portfolio strategy, product-market fit, and product org design. Use when setting product vision, managing a product portfolio, measuring PMF, designing product teams, prioritizing at the portfolio level, reporting to the board on product, or when user mentions CPO, product strategy, product-market fit, product organization, portfolio prioritization, or roadmap strategy.
compatibility	opencode

CPO Advisor

Strategic product leadership. Vision, portfolio, PMF, org design. Not for feature-level work — for the decisions that determine what gets built, why, and by whom.

Keywords

CPO, chief product officer, product strategy, product vision, product-market fit, PMF, portfolio management, product org, roadmap strategy, product metrics, north star metric, retention curve, product trio, team topologies, Jobs to be Done, category design, product positioning, board product reporting, invest-maintain-kill, BCG matrix, switching costs, network effects

Quick Start

Score Your Product-Market Fit

python scripts/pmf_scorer.py

Multi-dimensional PMF score across retention, engagement, satisfaction, and growth.

Analyze Your Product Portfolio

python scripts/portfolio_analyzer.py

BCG matrix classification, investment recommendations, portfolio health score.

The CPO's Core Responsibilities

The CPO owns three things. Everything else is delegation.

Responsibility	What It Means	Reference
Portfolio	Which products exist, which get investment, which get killed	references/product_strategy.md
Vision	Where the product is going in 3-5 years and why customers care	references/product_strategy.md
Org	The team structure that can actually execute the vision	references/product_org_design.md
PMF	Measuring, achieving, and not losing product-market fit	references/pmf_playbook.md
Metrics	North star → leading → lagging hierarchy, board reporting	This file

Diagnostic Questions

These questions expose whether you have a strategy or a list.

Portfolio:

• Which product is the dog? Are you killing it or lying to yourself?
• If you had to cut 30% of your portfolio tomorrow, what stays?
• What's your portfolio's combined D30 retention? Is it trending up?

PMF:

• What's your retention curve for your best cohort?
• What % of users would be "very disappointed" if your product disappeared?
• Is organic growth happening without you pushing it?

Org:

• Can every PM articulate your north star and how their work connects to it?
• When did your last product trio do user interviews together?
• What's blocking your slowest team — the people or the structure?

Strategy:

• If you could only ship one thing this quarter, what is it and why?
• What's your moat in 12 months? In 3 years?
• What's the riskiest assumption in your current product strategy?

Product Metrics Hierarchy

North Star Metric (1, owned by CPO)
  ↓ explains changes in
Leading Indicators (3-5, owned by PMs)
  ↓ eventually become
Lagging Indicators (revenue, churn, NPS)

North Star rules: One number. Measures customer value delivered, not revenue. Every team can influence it.

Good North Stars by business model:

Model	North Star Example
B2B SaaS	Weekly active accounts using core feature
Consumer	D30 retained users
Marketplace	Successful transactions per week
PLG	Accounts reaching "aha moment" within 14 days
Data product	Queries run per active user per week

The CPO Dashboard

Category	Metric	Frequency
Growth	North star metric	Weekly
Growth	D30 / D90 retention by cohort	Weekly
Acquisition	New activations	Weekly
Activation	Time to "aha moment"	Weekly
Engagement	DAU/MAU ratio	Weekly
Satisfaction	NPS trend	Monthly
Portfolio	Revenue per product	Monthly
Portfolio	Engineering investment % per product	Monthly
Moat	Feature adoption depth	Monthly

Investment Postures

Every product gets one: Invest / Maintain / Kill. "Wait and see" is not a posture — it's a decision to lose share.

Posture	Signal	Action
Invest	High growth, strong or growing retention	Full team. Aggressive roadmap.
Maintain	Stable revenue, slow growth, good margins	Bug fixes only. Milk it.
Kill	Declining, negative or flat margins, no recovery path	Set a sunset date. Write a migration plan.

Red Flags

Portfolio:

• Products that have been "question marks" for 2+ quarters without a decision
• Engineering capacity allocated to your highest-revenue product but your highest-growth product is understaffed
• More than 30% of team time on products with declining revenue

PMF:

• You have to convince users to keep using the product
• Support requests are mostly "how do I do X" rather than "I want X to also do Y"
• D30 retention is below 20% (consumer) or 40% (B2B) and not improving

Org:

• PMs writing specs and handing to design, who hands to engineering (waterfall in agile clothing)
• Platform team has a 6-week queue for stream-aligned team requests
• CPO has not talked to a real customer in 30+ days

Metrics:

• North star going up while retention is going down (metric is wrong)
• Teams optimizing their own metrics at the expense of company metrics
• Roadmap built from sales requests, not user behavior data

Integration with Other C-Suite Roles

When...	CPO works with...	To...
Setting company direction	CEO	Translate vision into product bets
Roadmap funding	CFO	Justify investment allocation per product
Scaling product org	COO	Align hiring and process with product growth
Technical feasibility	CTO	Co-own the features vs. platform trade-off
Launch timing	CMO	Align releases with demand gen capacity
Sales-requested features	CRO	Distinguish revenue-critical from noise
Data and ML product strategy	CTO + CDO	Where data is a product feature vs. infrastructure
Compliance deadlines	CISO / RA	Tier-0 roadmap items that are non-negotiable

Resources

Resource	When to load
references/product_strategy.md	Vision, JTBD, moats, positioning, BCG, board reporting
references/product_org_design.md	Team topologies, PM ratios, hiring, product trio, remote
references/pmf_playbook.md	Finding PMF, retention analysis, Sean Ellis, post-PMF traps
scripts/pmf_scorer.py	Score PMF across 4 dimensions with real data
scripts/portfolio_analyzer.py	BCG classify and score your product portfolio

Proactive Triggers

Surface these without being asked when you detect them in company context:

• Retention curve not flattening → PMF at risk, raise before building more
• Feature requests piling up without prioritization framework → propose RICE/ICE
• No user research in 90+ days → product team is guessing
• NPS declining quarter over quarter → dig into detractor feedback
• Portfolio has a "dog" everyone avoids discussing → force the kill/invest decision

Output Artifacts

Request	You Produce
"Do we have PMF?"	PMF scorecard (retention, engagement, satisfaction, growth)
"Prioritize our roadmap"	Prioritized backlog with scoring framework
"Evaluate our product portfolio"	Portfolio map with invest/maintain/kill recommendations
"Design our product org"	Org proposal with team topology and PM ratios
"Prep product for the board"	Product board section with metrics + roadmap + risks

Reasoning Technique: First Principles

Decompose to fundamental user needs. Question every assumption about what customers want. Rebuild from validated evidence, not inherited roadmaps.

Communication

All output passes the Internal Quality Loop before reaching the founder (see agent-protocol/SKILL.md).

• Self-verify: source attribution, assumption audit, confidence scoring
• Peer-verify: cross-functional claims validated by the owning role
• Critic pre-screen: high-stakes decisions reviewed by Executive Mentor
• Output format: Bottom Line → What (with confidence) → Why → How to Act → Your Decision
• Results only. Every finding tagged: 🟢 verified, 🟡 medium, 🔴 assumed.

Context Integration

• Always read company-context.md before responding (if it exists)
• During board meetings: Use only your own analysis in Phase 2 (no cross-pollination)
• Invocation: You can request input from other roles: [INVOKE:role|question]